Rapid color classification and quantification of Chinese cabbage leaf based on multispectral technique
In order to solve the problems of strong subjectivity,slow speed and low efficiency in manual identification of leaf color of Chinese cabbage,this study proposed a method of rapid and accurate classification and quantification of leaf color of Chinese cabbage by combining multi-spectral image processing with machine vision technology.The results showed that the original spectral data extracted by the 19-channel multispectral system contained more comprehensive and accurate information,and the SVM classification model established by the system showed the best classification effect.The accuracy of training set was 98.24%,and the accuracy of verification set was 87.18%.The continuous projection algorithm(SPA)was used to extract characteristic wavelength for analysis,and the Chinese cabbage samples collected by a 5-channel camera were selected to continue to continuously study the quantification of leaf color of Chinese cabbage.By extracting the RGB,HSV,LAB nine color feature values for data processing,the color of Chinese cabbage leaves can be accurately quantized by 0-100 values.
NETL
NSTL
万方数据
